Static Versus Dynamic Decoding Algorithms in a Non-Invasive Body-Machine Interface.

In this study, we consider a non-invasive body-machine interface that captures body motions still available to people with spinal cord injury (SCI) and maps them into a set of signals for controlling a computer user interface while engaging in a sustained level of mobility and exercise. We compare the effectiveness of two decoding algorithms that transform a high-dimensional body-signal vector into a lower dimensional control vector on six subjects with high-level SCI and eight controls. One algorithm is based on a static map from current body signals to the current value of the control vector set through principal component analysis (PCA), the other on dynamic mapping a segment of body signals to the value and the temporal derivatives of the control vector set through a Kalman filter. SCI and control participants performed straighter and smoother cursor movements with the Kalman algorithm during center-out reaching, but their movements were faster and more precise when using PCA. All participants were able to use the BMI's continuous, two-dimensional control to type on a virtual keyboard and play pong, and performance with both algorithms was comparable. However, seven of eight control participants preferred PCA as their method of virtual wheelchair control. The unsupervised PCA algorithm was easier to train and seemed sufficient to achieve a higher degree of learnability and perceived ease of use.

Using noise to shape motor learning.

Each of our movements is selected from any number of alternative movements. Some studies have shown evidence that the central nervous system (CNS) chooses to make the specific movements that are least affected by motor noise. Previous results showing that the CNS has a natural tendency to minimize the effects of noise make the direct prediction that if the relationship between movements and noise were to change, the specific movements people learn to make would also change in a predictable manner. Indeed, this has been shown for well-practiced movements such as reaching. Here, we artificially manipulated the relationship between movements and visuomotor noise by adding noise to a motor task in a novel redundant geometry such that there arose a single control policy that minimized the noise. This allowed us to see whether, for a novel motor task, people could learn the specific control policy that minimized noise or would need to employ other compensation strategies to overcome the added noise. As predicted, subjects were able to learn movements that were biased toward the specific ones that minimized the noise, suggesting not only that the CNS can learn to minimize the effects of noise in a novel motor task but also that artificial visuomotor noise can be a useful tool for teaching people to make specific movements. Using noise as a teaching signal promises to be useful for rehabilitative therapies and movement training with human-machine interfaces. NEW & NOTEWORTHY: Many theories argue that we choose to make the specific movements that minimize motor noise. Here, by changing the relationship between movements and noise, we show that people actively learn to make movements that minimize noise. This not only provides direct evidence for the theories of noise minimization but presents a way to use noise to teach specific movements to improve rehabilitative therapies and human-machine interface control.

Body-Machine Interfaces after Spinal Cord Injury: Rehabilitation and Brain Plasticity.

The purpose of this study was to identify rehabilitative effects and changes in white matter microstructure in people with high-level spinal cord injury following bilateral upper-extremity motor skill training. Five subjects with high-level (C5-C6) spinal cord injury (SCI) performed five visuo-spatial motor training tasks over 12 sessions (2-3 sessions per week). Subjects controlled a two-dimensional cursor with bilateral simultaneous movements of the shoulders using a non-invasive inertial measurement unit-based body-machine interface. Subjects' upper-body ability was evaluated before the start, in the middle and a day after the completion of training. MR imaging data were acquired before the start and within two days of the completion of training. Subjects learned to use upper-body movements that survived the injury to control the body-machine interface and improved their performance with practice. Motor training increased Manual Muscle Test scores and the isometric force of subjects' shoulders and upper arms. Moreover, motor training increased fractional anisotropy (FA) values in the cingulum of the left hemisphere by 6.02% on average, indicating localized white matter microstructure changes induced by activity-dependent modulation of axon diameter, myelin thickness or axon number. This body-machine interface may serve as a platform to develop a new generation of assistive-rehabilitative devices that promote the use of, and that re-strengthen, the motor and sensory functions that survived the injury.

Upper Body-Based Power Wheelchair Control Interface for Individuals With Tetraplegia.

Many power wheelchair control interfaces are not sufficient for individuals with severely limited upper limb mobility. The majority of controllers that do not rely on coordinated arm and hand movements provide users a limited vocabulary of commands and often do not take advantage of the user's residual motion. We developed a body-machine interface (BMI) that leverages the flexibility and customizability of redundant control by using high dimensional changes in shoulder kinematics to generate proportional control commands for a power wheelchair. In this study, three individuals with cervical spinal cord injuries were able to control a power wheelchair safely and accurately using only small shoulder movements. With the BMI, participants were able to achieve their desired trajectories and, after five sessions driving, were able to achieve smoothness that was similar to the smoothness with their current joystick. All participants were twice as slow using the BMI however improved with practice. Importantly, users were able to generalize training controlling a computer to driving a power wheelchair, and employed similar strategies when controlling both devices. Overall, this work suggests that the BMI can be an effective wheelchair control interface for individuals with high-level spinal cord injuries who have limited arm and hand control.

Remapping residual coordination for controlling assistive devices and recovering motor functions.

The concept of human motor redundancy attracted much attention since the early studies of motor control, as it highlights the ability of the motor system to generate a great variety of movements to achieve any well-defined goal. The abundance of degrees of freedom in the human body may be a fundamental resource in the learning and remapping problems that are encountered in human-machine interfaces (HMIs) developments. The HMI can act at different levels decoding brain signals or body signals to control an external device. The transformation from neural signals to device commands is the core of research on brain-machine interfaces (BMIs). However, while BMIs bypass completely the final path of the motor system, body-machine interfaces (BoMIs) take advantage of motor skills that are still available to the user and have the potential to enhance these skills through their consistent use. BoMIs empower people with severe motor disabilities with the possibility to control external devices, and they concurrently offer the opportunity to focus on achieving rehabilitative goals. In this study we describe a theoretical paradigm for the use of a BoMI in rehabilitation. The proposed BoMI remaps the user's residual upper body mobility to the two coordinates of a cursor on a computer screen. This mapping is obtained by principal component analysis (PCA). We hypothesize that the BoMI can be specifically programmed to engage the users in functional exercises aimed at partial recovery of motor skills, while simultaneously controlling the cursor and carrying out functional tasks, e.g. playing games. Specifically, PCA allows us to select not only the subspace that is most comfortable for the user to act upon, but also the degrees of freedom and coordination patterns that the user has more difficulty engaging. In this article, we describe a family of map modifications that can be made to change the motor behavior of the user. Depending on the characteristics of the impairment of each high-level spinal cord injury (SCI) survivor, we can make modifications to restore a higher level of symmetric mobility (left versus right), or to increase the strength and range of motion of the upper body that was spared by the injury. Results showed that this approach restored symmetry between left and right side of the body, with an increase of mobility and strength of all the degrees of freedom in the participants involved in the control of the interface. This is a proof of concept that our BoMI may be used concurrently to control assistive devices and reach specific rehabilitative goals. Engaging the users in functional and entertaining tasks while practicing the interface and changing the map in the proposed ways is a novel approach to rehabilitation treatments facilitated by portable and low-cost technologies.

Combined Auditory and Vibrotactile Feedback for Human-Machine-Interface Control.

The purpose of this study was to determine the effect of the addition of binary vibrotactile stimulation to continuous auditory feedback (vowel synthesis) for human-machine interface (HMI) control. Sixteen healthy participants controlled facial surface electromyography to achieve 2-D targets (vowels). Eight participants used only real-time auditory feedback to locate targets whereas the other eight participants were additionally alerted to having achieved targets with confirmatory vibrotactile stimulation at the index finger. All participants trained using their assigned feedback modality (auditory alone or combined auditory and vibrotactile) over three sessions on three days and completed a fourth session on the third day using novel targets to assess generalization. Analyses of variance performed on the 1) percentage of targets reached and 2) percentage of trial time at the target revealed a main effect for feedback modality: participants using combined auditory and vibrotactile feedback performed significantly better than those using auditory feedback alone. No effect was found for session or the interaction of feedback modality and session, indicating a successful generalization to novel targets but lack of improvement over training sessions. Future research is necessary to determine the cognitive cost associated with combined auditory and vibrotactile feedback during HMI control.

A body machine interface based on inertial sensors.

Spinal cord injury (SCI) survivors generally retain residual motor and sensory functions, which provide them with the means to control assistive devices. A body-machine interface (BoMI) establishes a mapping from these residual body movements to control commands for an external device. In this study, we designed a BoMI to smooth the way for operating computers, powered wheelchairs and other assistive technologies after cervical spinal cord injuries. The interface design included a comprehensive training paradigm with a range of diverse functional activities to enhance motor learning and retention. Two groups of SCI survivors and healthy control subjects participated in the study. The results indicate the effectiveness of the developed system as an alternative pathway for individuals with motor disabilities to control assistive devices while engaging in functional motor activity.

Comparison of nasal acceleration and nasalance across vowels.

PURPOSE: The purpose of this study was to determine the performance of normalized nasal acceleration (NNA) relative to nasalance as estimates of nasalized versus nonnasalized vowel and sentence productions. METHOD: Participants were 18 healthy speakers of American English. NNA was measured using a custom sensor, and nasalance was measured using the KayPentax Nasometer II. Speech stimuli consisted of CVC syllables with the vowels (//, /æ/, /i/, /u/) and sentences loaded with high front, high back, low front, and low back vowels in both nasal and nonnasal contexts. RESULTS: NNA showed a small but significant effect of the vowel produced during syllable stimuli but no significant effect of vowel loading during sentence stimuli. Nasalance was significantly affected by the vowel being produced during both syllables and sentences with large effect sizes. Both NNA and nasalance were highly sensitive and specific to nasalization. CONCLUSIONS: NNA was less affected by vowel than nasalance. Discrimination of nasal versus nonnasal stimuli using NNA and nasalance was comparable, suggesting potential for use of NNA for biofeedback applications. Future work to improve calibration of NNA is needed to lower intersubject variability.

Normalization strategies for nasal acceleration to assess velopharyngeal function.

Velopharyngeal function is essential for intelligible speech production, but can often be impaired. Current clinical care could be improved with the use of reliable and objective methods of assessment appropriate for home use. This paper explores the use of a combined nasal acceleration and acoustic sensor to assess velopharyngeal function. Speech production data in nasalized and non-nasalized contexts is recorded from N=6 healthy participants and three normalization strategies are assessed. Normalizing data to maximally nasal productions results in a reduction of between-speaker variability. Using a filtered speech signal can reduce the effects of intra-speaker variability caused be differences in loudness. The normalization strategies pursued show high discriminability of nasalization in vowels with an inexpensive sensor appropriate for home use.